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Implications of real-time data for forecasting and modeling expectations

  • Sharon Kozicki

This note extends the analysis in Stark and Croushore (2001) with an emphasis on the importance of data vintage for survey forecasts and modeling expectations. For both of these types of empirical exercises, results suggest that the choice of latest available or real-time data is critical for variables subject to large level revisions, but almost irrelevant for variables subject to only small revisions. Other forecasting practices were examined, with some surprising results.

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Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 01-12.

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Date of creation: 2001
Date of revision:
Handle: RePEc:fip:fedkrw:rwp01-12
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  1. Tom Stark and Dean Croushore, 2001. "Forecasting with a Real-Time Data Set for Macroeconomists," Computing in Economics and Finance 2001 258, Society for Computational Economics.
  2. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  3. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
  4. Sharon Kozicki & P.A. Tinsley, 1997. "Moving endpoints and the internal consistency of agents' ex ante forecasts," Research Working Paper 97-01, Federal Reserve Bank of Kansas City.
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